ACCES THE SEMINAR VIA TEAMS

Ulvick Houssou, PhD. Student, ICN Business School

Bio 

Ulvick Houssou is a PhD student at ICN Business School (France) on the theme of the entrepreneurial university. He is also responsible for monitoring-evaluation and quality assurance since 2015 at Senghor University in Alexandria (Egypt). His latest work focuses on the entrepreneurial practices of universities in the CAMES space as well as the evaluation mechanism of their entrepreneurial potential.

Entrepreneurial University in the CAMES area: An Exploratory Study

Abstract

The entrepreneurial university is recognized as an organization capable of maintaining an active link with the actors of its environment and of impacting socio-economic development. However, while it should be noted that the entrepreneurial university concept has been developed from the experience of advanced economies in the West, there is a lack of theoretical considerations and empirical evidence on whether the entrepreneurial university model is applicable in the contexts of less developed countries. Building on the understanding that the evolution of an ideal entrepreneurial university model is facilitated by certain institutional logics in advanced economies, this paper takes the case of CAMES area in Africa as an example to explore how the institutional logics in CAMES area are different from those of the developed countries and how the institutional logics in CAMES area would promote or hinder the development of entrepreneurial university model in Africa in light of an extensive review of the relevant literature and policy documents. Our study presents new possibilities of understanding for entrepreneurial university from Africa contexts. It suggests that to promote entrepreneurial university in CAMES area, policy makers and academics need to adjust some key factor of their institutional environments that can allow the emergence and the interaction of innovation actors more practical in local contexts. The conclusion reinforces the need to see entrepreneurial university through the lens of less developed countries contexts, highlighting opportunities for future studies.

Anicet Tchibozo, Ph.D. Student ICN Business School

Bio

Anicet is a Sr. Statistician and Epidemiologist with MSc degrees and Certificates from UCL (Belgium), Harvard School of Public Health (USA) and La Sorbonne (France). Since 1994, he has been providing Business Analytics consulting supports to Pharma, Financial and market research firms. He currently holds a Post hoc Analytics Expert for Health Economics and Value Added (HEVA) at SANOFI while completing his Ph.D program at ICN Business School. Anicet research interests cover, among others, applied Analytics, Big Data and Artificial intelligence to Management. Anicet is reviewer for BioMed Central (BMC) and has authored/co-authored articles published in journals such as Strategic HR Review, alth Systems, Biom Biostat Int J and Biomed Pap Med Fac Univ Palacky Olomouc Czech Repub.

Is the risk of Employee Absenteeism Predictable? The role of HR Analysis

Abstract

Absenteeism represents a major expense to most organizations (Park and Shauw, 2013; Jeswald, T. A., 1974). It is identified as one of the most proximal measures of organizational performance (Park and Shauw, (2013); Hancock, Julie I et al, 2013) and the most common dimension of work productivity (Hilton, Sheridan, Cleary and Whiteford, 2009). Therefore, there is an increasing call to strengthen the understanding of the individuals as well as the organizational mechanisms by which a single employee experiences absenteeism. In an evidence-based strategic Human Resource planning perspective, while (Lawrence, N.; Petrides, G. and Gerry, M. N., 2020) focused their research on a particular firm, this article aims to provide organizations with large-scale tools to tackle the main factors predicting absenteeism using a retrospective longitudinal design.

A sample of 8336 employees pulled from the different business units (BU) of a real Canadian firm of which the name is kept anonymous for ethical and law considerations was analyzed. A employee experienced absenteeism if his or her total annual absence hours was greater than zero (0). Risk factors of absence were assessed with Kaplan Meier estimator and Cox regression integrating parametric distribution.

Preliminary results suggest that age is a major factor in predicting absenteeism rate with gender playing a small part in one of the age ranges: >43 and <52 with males having a lower absence rate in this group. Almost none of the other categorical factors doesn’t seem to help in the prediction.

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